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Factor structural time series models for official statistics with an application to hours worked in Germany

Author

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  • Weigand, Roland

    (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])

  • Wanger, Susanne

    () (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])

  • Zapf, Ines

    () (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])

Abstract

"We introduce a high-dimensional structural time series model, where co-movement between the components is due to common factors. A two-step estimation strategy is presented, which is based on principal components in differences in a first step and state space methods in a second step. The methods add to the toolbox of official statisticians, constructing timely regular statistics from different data sources. In this context, we discuss typical measurement features such as survey errors, statistical breaks, different sampling frequencies and irregular observation patterns, and describe their statistical treatment. The methods are applied to the estimation of paid and unpaid overtime work as well as flows on working-time accounts in Germany, which enter the statistics on hours worked in the national accounts." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Weigand, Roland & Wanger, Susanne & Zapf, Ines, 2015. "Factor structural time series models for official statistics with an application to hours worked in Germany," IAB Discussion Paper 201522, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Handle: RePEc:iab:iabdpa:201522
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    References listed on IDEAS

    as
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    6. John Wood & Duncan Elliott, 2007. "Methods explained: forecasting," Economic & Labour Market Review, Palgrave Macmillan;Office for National Statistics, vol. 1(12), pages 55-58, December.
    7. Andrew Harvey & Chia‐Hui Chung, 2000. "Estimating the underlying change in unemployment in the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 303-309.
    8. Schanne, Norbert, 2015. "A Global Vector Autoregression (GVAR) model for regional labour markets and its forecasting performance with leading indicators in Germany," IAB Discussion Paper 201513, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    9. Pfeffermann, Danny, 1991. "Estimation and Seasonal Adjustment of Population Means Using Data from Repeated Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 177-177, April.
    10. Susanne Wanger & Roland Weigand & Ines Zapf, 2016. "Measuring hours worked in Germany – Contents, data and methodological essentials of the IAB working time measurement concept
      [Die Berechnung der geleisteten Arbeitsstunden in Deutschland – Inhalte,
      ," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(3), pages 213-238, November.
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    Cited by:

    1. Susanne Wanger & Roland Weigand & Ines Zapf, 2016. "Measuring hours worked in Germany – Contents, data and methodological essentials of the IAB working time measurement concept
      [Die Berechnung der geleisteten Arbeitsstunden in Deutschland – Inhalte,
      ," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(3), pages 213-238, November.

    More about this item

    Keywords

    IAB-Arbeitszeitrechnung - Methode; Arbeitszeit; Arbeitsvolumen; Zeitreihenanalyse; Schätzung; Methodenliteratur; Überstunden; Arbeitszeitkonto;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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